Clinical trial data analysis using R [electronic resource] / Ding-Geng (Din) Chen, Karl E. Peace.

By: Chen, Ding-GengContributor(s): Peace, Karl E, 1941-Material type: Text

TextSeries: Chapman & Hall/CRC biostatistics seriesPublication details: Boca Raton : CRC Press, 2011. Description: xxiii, 363 p. : illISBN: 9781439840214 (ebook : PDF)Subject(s): Clinical trials -- Statistical methods | R (Computer program language)Genre/Form: Electronic books.Additional physical formats: No titleOnline resources: Click here to access online Also available in print edition.

Contents:

1. Introduction to R -- 2. Overview of clinical trials -- 3. Treatment comparisons in clinical trials -- 4. Treatment comparisons in clinical trials with covariates -- 5. Analysis of clinical trials with time-to-event endpoints -- 6. Analysis of data from longitudinal clinical trials -- 7. Sample size determination and power calculation in clinical trials -- 8. Meta-analysis of clinical trials -- 9. Bayesian analysis methods in clinical trials -- 10. Analysis of bioequivalence clinical trials -- 11. Analysis of adverse events in clinical trials -- 12. Analysis of DNA microarrays in clinical trials.

Summary: "With examples based on the authors' 30 years of real-world experience in many areas of clinical drug development, this book provides a thorough presentation of clinical trial methodology. It presents detailed step-by-step illustrations on the implementation of the open-source software R. Case studies demonstrate how to select the appropriate clinical trial data. The authors introduce the corresponding biostatistical analysis methods, followed by the step-by-step data analysis using R. They also offer the R program for download, along with other essential data, on their website"--Provided by publisher.

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Includes bibliographical references (p. 349-357) and index.

"With examples based on the authors' 30 years of real-world experience in many areas of clinical drug development, this book provides a thorough presentation of clinical trial methodology. It presents detailed step-by-step illustrations on the implementation of the open-source software R. Case studies demonstrate how to select the appropriate clinical trial data. The authors introduce the corresponding biostatistical analysis methods, followed by the step-by-step data analysis using R. They also offer the R program for download, along with other essential data, on their website"--Provided by publisher.